Dr. Susan Gruber is an Assistant Professor and Biostatistician in the Department of Population Medicine (DPM) at Harvard Medical School and the Harvard Pilgrim Health Care Institute. She is a leading expert on Targeted Learning, which combines targeted minimum loss-based estimation (TMLE) and data-adaptive Super Learning. Her work focuses on methods development for detecting safety signals in electronic health data, and applications of machine learning in predictive modeling and propensity score estimation. Dr. Gruber wrote the first publicly available software for applying Targeted Learning in point treatment settings, and for estimating the marginal mean outcome of a multiple time-point intervention. She received her doctoral degree in Biostatistics from the University of California, Berkeley in 2011, and also holds an MPH in Epidemiology and Biostatistics, and an MS in Computer Science. Dr. Gruber is former Senior Director of IMEDS- Methods Research for the Reagan-Udall Foundation for the FDA.